Interval Scheduling Algorithm

Author: Vinay Sanwal

scheduling/Iinterval_scheduling_algorithm.py

@@ -0,0 +1,32 @@
+"""
+interval scheduling is a class of problems. The programs take a number of tasks into account. Every task is represented by an interval that indicates the amount of time it should take a machine to complete it. If there is no overlap between any two intervals on the system or resource, a subset of intervals is compatible.
+
+The goal of the interval scheduling maximization problem is to identify the largest compatible set or a collection of intervals with the least possible overlap. The idea is to optimize throughput by completing as many tasks as you can.
+
+"""
+
+def interval_scheduling(stimes, ftimes):
+    index = list(range(len(stimes)))
+    # sort according to finish times
+    index.sort(key=lambda i: ftimes[i])
+ 
+    maximal_set = set()
+    prev_finish_time = 0
+    for i in index:
+        if stimes[i] >= prev_finish_time:
+            maximal_set.add(i)
+            prev_finish_time = ftimes[i]
+ 
+    return maximal_set
+ 
+ 
+n = int(input('Enter number of activities: '))
+stimes = input('Enter the start time of the {} activities in order: '
+              .format(n)).split()
+stimes = [int(st) for st in stimes]
+ftimes = input('Enter the finish times of the {} activities in order: '
+               .format(n)).split()
+ftimes = [int(ft) for ft in ftimes]
+ 
+ans = interval_scheduling(stimes, ftimes)
+print('A maximum-size subset of activities that are mutually compatible is', ans)